Natural Language Processing Engineer简历模板
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Peter Xiong
13800000000
zhangwei@example.com
Beijing
30
Male
Natural Language Processing Engineer
Employed
Beijing
25k-35kEducation Experience
2015.09
2018.06
Tsinghua University - Master985211
Computer Science and Technology
- Systematically studied the core courses of the Computer Science and Technology major, including Data Structure, Algorithm Design, Operating System, etc., laying a solid theoretical foundation for subsequent work in natural language processing.
- Participated in multiple course projects, such as the development of a small database management system based on Java, exercising programming ability and team collaboration ability.
Work Experience
2018.07
2021.12
Baidu - Artificial Intelligence Technology DepartmentInternet GiantTechnology-driven
Natural Language Processing EngineerDeep LearningNatural Language ProcessingKnowledge Graph
Beijing
- Responsible for the development and optimization of the company's core natural language processing projects. Based on deep learning frameworks TensorFlow/PyTorch, realized the model construction and training of multiple basic NLP tasks such as text classification and named entity recognition. The model accuracy rate was improved to the industry-leading level (such as the text classification accuracy rate was increased from 85% to 92%).
- Participated in the company's knowledge graph project, responsible for the development of the entity relationship extraction module. Through optimizing algorithms and data augmentation strategies, the recall rate of relationship extraction was increased by 15%, providing high-quality data support for the construction of the knowledge graph.
- Closely cooperated with the product team, applied natural language processing technology to the company's intelligent customer service system, realized a significant improvement in the intention recognition accuracy rate (from 70% to 85%), effectively reducing the workload of manual customer service and improving customer satisfaction.
2022.01
至今
ByteDance - Language Technology TeamInnovative EnterpriseRapid Development
Senior Natural Language Processing EngineerPre-trained ModelIntelligent WritingMachine Translation
Beijing
- Led the R & D of the natural language processing module of the company's new-generation intelligent writing platform. Introduced pre-trained language models (such as GPT series). Through fine-tuning and optimization, the fluency and relevance of the generated text were greatly improved, and user satisfaction was increased by 30%.
- Responsible for building the company's internal natural language processing toolchain, including text preprocessing, word vector training, model evaluation and other modules, which improved the team's development efficiency by more than 30%.
- Led the team to participate in the tackling of multiple important projects, such as the multilingual machine translation system (supporting mutual translation among Chinese, English, Japanese, Korean and other languages). Through optimizing the neural network architecture and data processing flow, the translation quality (BLEU value) was increased by 10%, and it was successfully applied to the company's cross-border e-commerce business, helping the business expansion.
Project Experience
2019.05
2020.12
Intelligent Public Opinion Analysis System - Baidu
Core Developer
- This project aims to build an intelligent public opinion analysis system based on natural language processing, providing real-time public opinion monitoring and analysis services for enterprises.
- I served as the core developer, responsible for the R & D of the text sentiment analysis module. Adopted deep learning models (such as LSTM + Attention mechanism), combined with large-scale annotated data for training. Through data augmentation (such as back-translation, synonym replacement, etc.) and model tuning, the sentiment analysis accuracy rate reached more than 90%.
- After the system was launched, it successfully monitored multiple negative public opinion events of enterprises, providing strong support for enterprises to take timely countermeasures and helping enterprises recover millions of yuan in economic losses.
2022.03
至今
Intelligent Question-answering System - ByteDance
Module Leader
- Participated in the development of the intelligent question-answering system project, aiming to provide users with accurate and fast question-answering services.
- I was responsible for the question understanding and answer generation modules. In question understanding, used named entity recognition, syntactic analysis and other technologies to accurately extract key information of questions; in answer generation, combined knowledge graph and deep learning models (such as Transformer) to generate high-quality answers.
- In the internal test of the system, the answer accuracy rate reached more than 80%. After the launch, it processed more than 100,000 user question-answering requests per day on average, effectively improving the efficiency of users obtaining information.
Personal Summary
- With years of R & D experience in the field of natural language processing, proficient in deep learning frameworks (TensorFlow/PyTorch) and natural language processing algorithms (such as BERT, GPT, etc.).
- Possess rich project practical experience, control the whole process from requirement analysis to system launch, and successfully delivered multiple natural language processing projects with commercial value.
- Good team collaboration and communication skills, able to lead the team to overcome technical problems and promote project progress.
- Continuously pay attention to the cutting-edge technology trends in the industry, keep learning and innovating, and inject new technical vitality into the company's products.
Honor Awards
Baidu 2020 Excellent Employee
ByteDance 2022 Technology Innovation Award
Other Information
Open-source Contribution:
- Actively participated in the open-source community, contributed multiple code repositories related to natural language processing on GitHub (such as text classification sample code based on PyTorch, a simple version of knowledge graph construction tool), and accumulated hundreds of stars, providing learning and reference resources for community developers.
